Development of the novelty order allocation model based on supplier's willingness – Combination of a Bayesian network and a stochastic multi-objective linear programming

Abstract

The aim of this study is to develop a novelty order allocation through combination of a Bayesian network and a stochastic multi-objective linear programming model to help manufacturers with order allocation decisions under the uncertainty of supplier's willingness to cooperate. In this paper, we deal with the uncertainty of the willingness to cooperate through several phases. The first phase presents the determination of the factors influencing willingness to cooperate. Then Bayesian network theory is used to deal with the uncertainty of willingness to cooperate and transformation into scenarios. Finally, a stochastic multi-objective linear programming model is developed, and the weighted-sum method is utilized to solve the model. The results demonstrate the feasibility of the approaches. The order allocation model based on supplier's willingness to cooperate proposed in this paper expands the research field and reduces the carbon emission management risk of manufacturers due to the change of supplier's willingness to cooperate.